Deep Memory Hierarchies

RSVP: I/O staging for extreme scale data

RSVP: Runtime System for I/O staging in support of Voluminous in situ Processing of extreme scale data

At these extreme scales, online data processing pipelines will need to be easily and dynamically composed, efficiently executed alongside the scientific simulations producing the data, and support reuse of computation and data. Furthermore, the need to seamlessly integrate experimental data is imposing additional demands on extreme-scale datamanagement solutions. The overarching goal of the RSVP project is to fundamentally address these challenges by developing model in which computational, data transformation and data analytic services can be easily and efficiently associated with and applied to science data as part of an end-to-end, in situ “process flow.”

Heterogeneous Platforms and Systems

Heterogeneous Platforms and Systems are becoming the norm for mobile devices, server systems, and large-scale machines. This project investigates system support to exploit and deal with heterogeneity, at levels of abstraction ranging from middleware, to toolchains, to instrumentation, and operating systems. Concerning individual platforms, our research targets heterogeneous platforms with multicore CPUs and/or integrated and discrete GPUs, and the complex memory systems of future large-memory servers with on-chip fast RAM, die-stacked RAM, NVRAM, and SSD memories. Concerning larger-scale systems, we are considering cloud-hosting datacenters and high end machines like those planned for the exascale era.

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